Systems and methods for anatomical modeling using information obtained from a medical procedure

ABSTRACT

Systems and methods are disclosed herein for anatomical modeling using information obtained during a medical procedure, whereby an initial anatomical model is generated or obtained, a correspondence is determined between the initial model and additional data and/or measurements from an invasive or noninvasive procedure, and, if a discrepancy is found between the initial model and the additional data, the anatomical model is updated to incorporate the additional data and reduce the discrepancy.

PRIORITY

This application is a continuation of and claims the benefit of priorityto U.S. application Ser. No. 16/260,740, filed on Jan. 29, 2019, whichis a continuation of and claims the benefit of priority to U.S.application Ser. No. 15/347,592, filed on Nov. 9, 2016, now U.S. Pat.No. 10,236,084, issued Mar. 19, 2019, which claims the benefit ofpriority from U.S. Provisional Application No. 62/253,566, filed on Nov.10, 2015, which are incorporated by reference herein in theirentireties.

TECHNICAL FIELD

Various embodiments of the present disclosure relate generally tomedical imaging and related methods. More specifically, particularembodiments of the present disclosure relate to systems and methods foranatomical modeling using information obtained from a medical procedure.

BACKGROUND

Heart disease, such as coronary artery disease, may produce coronarylesions such as a stenosis (abnormal narrowing of a blood vessel) in theblood vessels that provide blood to and/or from the heart. As a result,blood flow to the heart may be restricted. A patient suffering fromcoronary artery disease may experience chest pain, referred to aschronic stable angina (during physical exertion) or unstable angina(when the patient is at rest). A more severe manifestation of diseasemay lead to myocardial infarction, or heart attack.

Anatomical modeling by noninvasive imaging may benefit a patient byassisting a physician in determining the severity of a disease and apossible treatment or treatments. Such noninvasive imaging andanatomical modeling may be performed using, for example, the systems andmethods described in U.S. Pat. No. 8,315,812, filed on Jan. 25, 2011 byCharles A. Taylor, which is incorporated by reference herein in itsentirety. Such anatomical modeling may be accompanied by, for example,automated identification of treatment options from a plurality offeasible treatment options (e.g., all possible percutaneous coronaryintervention (PCI) or coronary artery bypass grafting (CABG) options),by analyzing noninvasively assessed coronary anatomy, and automaticallydesigning, defining, or otherwise identifying a customized orpersonalized cardiac implant or other intervention for a specificpatient, by analyzing noninvasively assessed coronary anatomy. Forexample, a recommended treatment option may be generated by an automatedsystem, such as one or more of those described in, for example, U.S.Pat. No. 9,449,146, filed on Jul. 3, 2014 by Ryan Spilker et al., orU.S. Pat. No. 9,043,190, filed on Apr. 16, 2014 by Leo Grady et al, bothof which are incorporated by reference herein in their entireties.

In addition to being subjected to noninvasive imaging that may be usedto model and assess their coronary anatomy, patients suffering fromchest pain and/or exhibiting symptoms of coronary artery disease may besubjected to one or more invasive or noninvasive procedures that mayprovide supplemental, more accurate, and/or more current data relatingto coronary lesions and/or the anatomy of the heart. Such procedures mayinclude, for example, electrocardiograms, biomarker evaluation fromblood tests, treadmill tests, echocardiography, single positron emissioncomputed tomography (SPECT), positron emission tomography (PET), andcoronary computed tomographic angiography (CCTA). Moreover, if a patienthas been determined to require interventional treatment, additionalmeasurements may be taken via invasive or noninvasive methods during aninterventional procedure (e.g., via angiogram, pressure wire, opticalcoherence tomography (OCT), intravascular ultrasound (IVUS), flowmeters, intravascular optical imaging, external cameras in theinterventional suite or operating room, etc.).

Cardiologists and other health care professionals may analyze images,models and/or other data obtained prior to an interventional and/ordiagnostic procedure, when determining if and whether a suitableintervention for improving a patient's cardiovascular blood flow isnecessary. However, when such data are obtained prior to aninterventional and/or diagnostic procedure, their accuracy and/orprecision may vary, e.g., over time as a patient's system changes orages. Data obtained during an interventional and/or diagnosticprocedure, in contrast, may be more accurate and/or more current, butmay not provide a holistic view of the patient's system. Moreover,cardiologists and other medical professionals may not be able to conductan analysis and interpretation of such data in order to make anassessment of, and make decisions for further interventional measuresbased on, such data, while simultaneously performing a diagnostic and/orinterventional procedure.

A need exists for anatomical modeling using information obtained duringa medical procedure. In addition, a need exists for a system and methodfor providing an updated anatomical model, one or more modeledinterventional procedures, one or more recommended procedures based onthe updated anatomical model, and/or one or more modeled interventionalprocedures to a physician or other medical professional during a medicalprocedure, using information obtained during the medical procedure.

SUMMARY

In some embodiments of the present disclosure, systems and methods aredisclosed for anatomical modeling using information obtained during amedical procedure. In some embodiments, a method of automaticallyupdating a cardiovascular model includes receiving an anatomical modelof at least one cardiovascular vessel; receiving at least onecharacteristic associated with the anatomical model, transmitting arepresentation of at least one of the anatomical model or the at leastone associated characteristic to a display unit, receiving additionalpatient-specific data relating to the anatomical model from a medicalprocedure, determining a correspondence between the additionalpatient-specific data and at least one of the anatomical model or the atleast one associated characteristic, identifying a discrepancy betweenthe additional patient-specific data and at least one of the anatomicalmodel or the at least one associated characteristic, modifying at leastone of the anatomical model or the at least one associatedcharacteristic to reduce the discrepancy, and transmitting an updatedrepresentation of at least one of the anatomical model or the at leastone associated characteristic to the display unit.

In some embodiments, the method includes modeling an intervention or apart thereof on the anatomical model and transmitting a representationof the modeled intervention or part thereof to the display unit. In someembodiments, the method includes generating at least one recommendationof an intervention on the patient based on at least one of thethree-dimensional anatomical model or the at least one associatedcharacteristic, and transmitting the at least one recommendation to thedisplay unit. In some embodiments, the intervention is one or more of:insertion of an endoscopic device, a laparoscopic device, a stent, aprosthetic implant, a graft, or a needle; a bypass grafting procedure; arotablation; an atherectomy; an angioplasty; an endarterectomy; apercutaneous coronary intervention; a carotid intervention; a peripheralintervention; a renal revascularization; a mesenteric revascularization;or an arteriovenous access procedure. In some embodiments, the medicalprocedure is an invasive procedure. In some embodiments, the medicalprocedure is a diagnostic procedure.

In some embodiments, the at least one associated characteristic is ablood flow characteristic, a location of one or more lesions orblockages, or a location of one or more interventional devices. In someembodiments, the additional patient-specific data includes at least oneof: data from an angiogram; data from optical coherence tomography; datafrom an intravenous ultrasound; blood pressure data; coronary flow data;cardiac contractility data; a measurement of a plaque; a local heartviability; data showing whether an occlusion is total or subtotal; datarelating to the patient's physiological state; data relating tomyocardial wall motions; stent position data; or data from apercutaneous coronary intervention. In some embodiments, determining acorrespondence between the additional patient-specific data and at leastone of the three-dimensional anatomical model or the at least oneassociated characteristic includes determining a location of theanatomical model to which the additional patient-specific data mayapply. In some embodiments, the display unit is located in a medicalfacility.

In some embodiments of the present disclosure, a computer-implementedmethod for automatically updating an anatomical model includes receivinga patient-specific anatomical model generated from noninvasive imagingdata, receiving at least one characteristic associated with theanatomical model, transmitting a representation of the anatomical modeland the at least one associated characteristic to a display device,receiving additional patient-specific data from an interventionalprocedure, determining a correspondence between the patient-specificdata and the anatomical model, locating a discrepancy between theadditional patient-specific data and at least one of the anatomicalmodel or the at least one associated characteristic, updating at leastone of the anatomical model or the at least one associatedcharacteristic to reduce the discrepancy, and transmitting an updatedrepresentation of at least one of the anatomical model or the at leastone associated characteristic to the display device.

In some embodiments, the at least one associated characteristic is ablood flow characteristic. In some embodiments, the computer-implementedmethod further includes modeling an intervention on the anatomicalmodel, and transmitting a representation of the modeled intervention tothe display unit. In some embodiments, the computer-implemented methodfurther includes: generating at least one recommendation of anintervention on the patient based on at least one of the anatomicalmodel or the at least one associated characteristic; and transmittingthe at least one recommendation to the display unit. In someembodiments, the computer-implemented method further includes:periodically receiving refreshed additional patient-specific data fromthe interventional procedure; monitoring for a new discrepancy betweenthe refreshed patient-specific data and at least one of the anatomicalmodel or the at least one associated characteristic; and if a newdiscrepancy is found, updating at least one of the anatomical model orthe at least one associated characteristic to reduce the newdiscrepancy, and transmitting an updated representation of at least oneof the anatomical model or the at least one associated characteristic tothe display device.

In some embodiments of the present disclosure, an anatomical modelingsystem includes a processor configured to receive a patient-specific,three-dimensional anatomical model of at least one cardiovascularvessel, receive at least one characteristic associated with theanatomical model, transmit a representation of at least one of thethree-dimensional anatomical model or the at least one associatedcharacteristic to a display unit, receive additional patient-specificdata relating to the anatomical model from a medical procedure,determine a correspondence between the additional patient-specific dataand at least one of the three-dimensional anatomical model or the atleast one associated characteristic, identify a discrepancy between thepatient-specific data and at least one of the three-dimensionalanatomical model or the at least one associated characteristic, modifyat least one of the three-dimensional anatomical model or the at leastone associated characteristic to reduce the discrepancy, and transmit anupdated representation of at least one of the three-dimensionalanatomical model or the at least one associated characteristic to thedisplay unit.

In some embodiments, the processor is further configured to:periodically receive refreshed additional patient-specific data from theinterventional procedure; monitor for a new discrepancy between therefreshed patient-specific data and at least one of thethree-dimensional anatomical model or the at least one associatedcharacteristic; and if a new discrepancy is found, update at least oneof the three-dimensional anatomical model or the at least one associatedcharacteristic to reduce the new discrepancy, and transmit an updatedrepresentation of at least one of the three-dimensional anatomical modelor the at least one associated characteristic to the display device. Insome embodiments, the at least one associated characteristic is a bloodflow characteristic. In some embodiments, the processor is furtherconfigured to generate a model of an intervention on the anatomicalmodel, and transmit a representation of the modeled intervention to thedisplay unit. In some embodiments, the processor is further configuredto generate at least one recommendation of an intervention on thepatient based on at least one of the three-dimensional anatomical modelor the at least one associated characteristic, and transmit the at leastone recommendation to the display unit.

Additional objects and advantages of the disclosed embodiments will beset forth in part in the description that follows, and in part will beapparent from the description, or may be learned by practice of thedisclosed embodiments. The objects and advantages of the disclosedembodiments will be realized and attained by means of the elements andcombinations particularly pointed out in the appended claims.

It is to be understood that both the foregoing general description andthe following detailed description are exemplary and explanatory onlyand are not restrictive of the disclosed embodiments, as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of this specification, illustrate various exemplary embodiments andtogether with the description, serve to explain the principles of thedisclosed embodiments.

FIG. 1 depicts a schematic diagram of an exemplary system and networkfor creating and updating an anatomical model using information from amedical procedure.

FIG. 2 depicts a more detailed schematic diagram of an exemplary systemand network for creating and updating an anatomical model usinginformation from a medical procedure.

FIG. 3 depicts a flow diagram of an exemplary method for creating andupdating an anatomical model using information from a medical procedure.

FIGS. 4A-4B depict a flow diagram of another exemplary method forcreating and updating an anatomical model using information from amedical procedure.

DESCRIPTION OF THE EMBODIMENTS

Reference will now be made in detail to the exemplary embodiments of theinvention, examples of which are illustrated in the accompanyingdrawings. Wherever possible, the same reference numbers will be usedthroughout the drawings to refer to the same or like parts.

The present disclosure is directed to anatomical modeling usinginformation from a medical procedure, such as coronary anatomicalmodeling using information from a diagnostic or interventional coronaryprocedure. In addition, the present disclosure is directed to modelinginterventional treatments using information from a medical procedure.Additionally, the disclosure may include a system and method formonitoring anatomical and/or physiological changes that occur during atreatment procedure (e.g., as a result of placing a stent or bypass) andupdating an anatomical and/or physiological model to reflect thechanges. Treatment recommendations and/or treatment rankings may also beupdated in response to updates to a patient anatomical and/orphysiological model to help a physician make decisions in treating apatient.

More specifically, the present disclosure is directed to systems andmethods for providing an updated anatomical model and treatment optionsusing anatomical data obtained via invasive or non-invasive medicalprocedures. The presently-disclosed systems and methods may receivepatient information (e.g., via medical imaging performed on thepatient), generate a patient-specific geometry of vessels, blood flow,and/or pathologies based on the patient information, and update suchpatient-specific geometry based on additional images, measurement ordata obtained during a medical procedure. Additionally, thepresently-disclosed systems and methods may model interventionalprocedures on updated patient-specific geometry, and/or may providerecommended treatment options based on updated patient-specific geometryand/or modeled interventional procedures on updated patient-specificgeometry.

For example, according to the present disclosure, an initial anatomicalmodel may be generated or obtained using, for example, non-invasiveimaging, a correspondence may be determined between the initial modeland additional data and/or measurements that are obtained during asubsequent invasive or noninvasive procedure, the initial model and theadditional data may be reviewed for discrepancies between the model andthe additional data, and if a discrepancy is found, the anatomical modelmay be updated to incorporate the additional data and reduce thediscrepancy. Such a method, and a system for performing such a method,may benefit cardiologists and other medical professionals who diagnose,plan, and perform treatments for patients with suspected diseases.

As another example, according to the present disclosure, an anatomicalmodel is generated or obtained using, for example, non-invasive imaging,an intervention is performed on a patient at a site relevant to theanatomical model, additional data and/or measurements are obtainedduring and/or after the intervention that reflect one or more changescaused by the intervention at the site relevant to the anatomical model,and the anatomical model is updated to incorporate the changes caused bythe intervention.

As a further example, according to the present disclosure, a system andmethod may be developed for providing an updated anatomical model, oneor more modeled interventional procedures, one or more recommendedprocedures based on the updated anatomical model, and/or one or moremodeled interventional procedures to a physician or other medicalprofessional during a medical procedure, using information obtainedduring the medical procedure, such that the physician or other medicalprofessional may have access to such an updated anatomical model, modelsof interventional procedures based on an updated anatomical model,and/or recommended procedures based on an updated anatomical model whileperforming an interventional procedure.

Referring now to the figures, FIG. 1 depicts a high-level schematicdiagram of an exemplary system and network for anatomical modeling usinginformation from a medical procedure. Specifically, FIG. 1 depicts aplurality of physician systems 102 and a plurality of third partyprovider systems 104, any of which may be connected to an electronicnetwork 101. Electronic network 101 may be, for example, a wired orwireless network of computer processors, electronic storage devices,etc., such as the Internet, a local area network, a wide area network,or any other computer network configuration known in the art. Theplurality of physician systems 102 and third party systems 104 may housevarious types of data such as, for example, measurement data 108,intervention data 110, and patient data 112. Such categories of data maybe related to a particular anatomical site in the human body, such asthe heart, and/or a particular system of the human body, such as thecardiovascular system, and/or a portion of a particular system of thehuman body, such as the heart and adjacent vasculature.

One or more server systems 106 may also be connected to the electronicnetwork 101, and may include various electronic devices and processorsfor storing, creating and manipulating images and data received, forexample, over the electronic network 101 from physician systems 102and/or third party systems 104. Server systems 106 may include, forexample, storage devices 120 for storing images and data, and processingdevices 122 for processing and manipulating images and data stored inthe storage devices 122. Server systems 106 may also include a modelingengine 114 which may create and/or update an anatomical model usingimages and data received over the electronic network 101 and/or storedin storage devices 120 and/or processed in processing devices 122, asdescribed further below. Server systems 106 may also include, forexample, an intervention engine 116, which may model potentialinterventional procedures on an anatomical model generated and/orupdated by modeling engine 114, and a recommendations engine 118 whichmay generate and/or update one or more recommendations of medicalprocedures based on an anatomical and/or physiological model generatedand/or updated by modeling engine 114 and/or intervention engine 116.Any of the devices and engines in the server systems 106 may also sendand/or receive data over the electronic network 101.

More specifically, physician systems 102 may include, for example,systems which collect and store data and medical records at medicaloffices, hospitals, and/or medical clinics, and diagnostic machines andsystems used by physicians. Examples of physician systems 102 which maycollect data include heart rate and blood pressure monitors, bloodanalysis equipment, electrocardiogram (ECG) machines, magnetic resonanceimaging (MRI) machines, computed tomography (CT) machines, PET scanners,SPECT scanners, OCT machines, IVUS machinery, pressure wires, and otherimaging devices. Examples of physician systems 102 which may store datainclude physician patient databases, computers, electronic patientmanagement systems, and medical records keeping systems.

Third party provider systems 104 may include, for example, systemsstoring data and medical records at additional institutions, e.g.,systems managed by diagnostic laboratories, academic institutions,insurance companies, medical instrument and/or implant manufacturers,etc. Third party provider systems 104 may also include imaging devicesand/or laboratory equipment. Physician systems 102 and/or third partyprovider systems 104 may collect data from, for example, patientappointments, patient examinations, medical imaging, medical records,medical interventions, questionnaires, laboratory tests, insurancerecords, product catalogues, and medical databases.

Measurement data 108 of physician systems 102 and/or third partyprovider systems 104 may include data taken invasively and/ornoninvasively from a patient using medical measurement devices, such astwo- and three-dimensional images of patent anatomy obtained via, forexample, CT scans, MRI procedures, PET scans, SPECT scans, and/or CCTA.CCTA may be used for imaging of patients with chest pain and involvesusing CT technology to image the heart and the coronary arteriesfollowing an intravenous infusion of a contrast agent. Additional datataken from a patient using medical measurement devices may include, forexample, blood pressure, blood viscosity, heart rate, ECGs, plateletcount, red blood cell count, biomarker evaluations, treadmill tests,echocardiography, angiograms, pressure wire measurements, OCT imagesand/or data, IVUS images and/or data, flow meter measurements,intravascular optical imaging, external cameras in an interventionalsuite/operating room, etc.

Intervention data 110 of physician systems 102 and/or third partyprovider systems 104 may include any data obtained around or during amedical procedure, e.g., interventions, such as intervention approachprocedures, appropriate loci for an intervention, indications for anintervention, the number of times an intervention has been performed ona patient and/or on a population of patients, success rates, cost, riskfactors, methods of performing an intervention, size and/or shape ofintervention tools, e.g., stents, wires, and the like, etc.

Patient data 112 of physician systems 102 and/or third party providersystems 104 may include additional information about a patient, such asage, sex, weight, race, ethnicity, height, family medical history,medical records, etc.

Physician systems 102 and/or third party provider systems 104 maytransmit, e.g., any of the above-described data to one another and/or toserver systems 106 over the electronic network 101. Server systems 106may be one or more computer processors and/or storage devices, which maybe interconnected via one or more wired or wireless electronicconnections. Server systems 106 may store data, including, e.g., images,received from physician systems 102 and/or third party provider systems104 in one or more storage devices 120.

Storage devices 120 may be one or more computers, computer processors,hard drives, cloud-based storage systems, and/or other system configuredto electronically store data and/or images. Storage devices 120 maystore received data in, for example, one or more databases, digital filesystems, and/or cloud-based storage systems. Further, the server systems106 may process received data in one or more processing devices 122.Processing devices 122 may process data by, for example, cataloguingreceived data, sorting data by one or more categories, such as bypatient, anatomical feature, intervention, measurement device, datecreated, date received, etc. Such processing may also include analyzingdata and/or selecting data to send to modeling engine 114, interventionengine 116, and/or recommendations engine 118. Storage devices 120and/or processing devices 122 may send received data, before or after itis stored and/or processed, to the modeling engine 114, the interventionengine 116, and/or the recommendations engine 118.

Storage devices 120, processing devices 122, modeling engine 114,invention engine 116, and recommendations engine 118 may each or all be,for example, one or more computer processors, computer storage devices,and/or combinations thereof. The modeling engine 114 may generate and/orupdate a three-dimensional anatomical model using relevant data receivedfrom the storage devices 120 and/or processing devices 122, via methodsthat are described in further detail below. The intervention engine 116may model an intervention on a three-dimensional anatomical model usingrelevant data received from the storage devices 120 and/or processingdevices 122, and/or using an anatomical model created or updated by themodeling engine 114, via methods that are also described in furtherdetail below. The recommendations engine 118 may generate one or morerecommended interventions based at least in part on the data receivedfrom the storage devices 120 and/or the processing devices 122, theanatomical model created or updated by the modeling engine 114, and/orone or more interventions modeled by the intervention engine 116.

Modeling engine 114, intervention engine 116, and recommendation engine118 may all be located on any hardware capable of allowing them toperform the functions described herein. For example, the modeling engine114, intervention engine 116, and recommendation engine 118 may alloperate on a single computer, or may be a set of networked computers,working, for example, in series or in parallel. In further embodiments,the functions of the modeling engine 114, intervention engine 116, andrecommendation engine 118 may be shared by two computational machines,or four or more computational machines.

FIG. 2 is another schematic diagram of an exemplary system 200 forgenerating and/or updating an anatomical model using data from a medicalprocedure. The system 200 may include, for example, storage devices 120and processing devices 122, which may be configured to send data andimages to the modeling engine 114, intervention engine 116 andrecommendation engine 118, all of which may be interconnected via one ormore wired or wireless connections (e.g., through an electronic network101). One or more interventional and/or measurement devices 204 may alsobe connected to the storage devices 120, processing devices 122,modeling engine 114, intervention engine 116 and/or recommendationengine 118. The modeling engine 114, intervention engine 116 and/orrecommendation engine 118 may also be electronically connected, via awired or wireless connection, to at least one terminal 206. The terminal206 may include a model display 210, and a recommendations display 208.In some embodiments, the system 200 may include one or more serversystems 106.

Interventional and/or measurement devices 204 may be any medical devicesconfigured to perform an intervention on, and/or take measurementsand/or readings from, a patient. For example, interventional devices mayinclude, e.g., endoscopic devices, laparoscopic devices, stents,prosthetic implants (e.g., prosthetic valves), grafts, and needles.Examples of measurement devices may include, e.g., image intensifiers,angiograms, pressure wires, OCT devices, IVUS devices, near-infraredspectroscopy (NIRS) devices, Raman spectroscopy (RS) devices, Dopplerwire, flow meters, ultrasound devices, intravascular optical imagingdevices, heart rate and blood pressure monitors, blood analysisequipment (e.g., equipment for measuring blood viscosity, plateletcount, red blood cell count, and/or biomarkers), electrocardiogram (ECG)machines, magnetic resonance imaging (MRI) machines, computed tomography(CT) machines, PET scanners, SPECT scanners, echocardiography machinery,treadmill test equipment, and/or external cameras in an interventionalsuite or operating room. Interventional and/or measurement devices 204may also be or include one or more computer processors, which may assistin taking and/or recording measurements, and/or transmittingmeasurements to storage devices 120, processing devices 122, modelingengine 114, interventions engine 116 and/or recommendations engine 118.Interventional and/or measurement devices 204 may be added to or removedfrom the system as needed.

Terminal 206 of system 200 may be located, for example, at the site of amedical procedure, or in a physician's office, hospital, examinationroom, or other location. Terminal 206 may include, for example, acomputer processor and at least one display screen, such as atelevision, computer screen, tablet screen, or other mobile devicescreen. In some embodiments, terminal 206 may be located adjacent to apatient for whom anatomical modeling is being used to diagnose and/ortreat the patient. In further embodiments, terminal 206 may be locatedin a physician office. In still further embodiments, terminal 206 may bea web browser-based terminal, and may be accessible via a user on, e.g.,a personal computer. In such embodiments, the browser-based terminal maybe secure, and may require, e.g., login or other credentials to beviewed. In further embodiments, system 200 may include more than oneterminal 206, each terminal 206 being located at a different location(e.g., one may be located adjacent to a patient; another may be locatedin a physician office; another may be a browser-based terminal, etc.).

The model display 210 may be, for example, a visual display of a modelreceived from the modeling engine 114 and/or the intervention engine116. In some embodiments, the model display 210 may be a two-dimensionalvisual representation of a three-dimensional model. In some embodiments,the model display 210 may be manipulable from terminal 206 or fromelsewhere. For example, a user, such as a physician, may use a keyboard,mouse, or touchscreen input to rotate, zoom in on, zoom out on, or viewdetails on parts of, the model display 210. In some embodiments, variouscharacteristics and measurements may be labeled in text form on themodel display 210, such as, for example, one or more blood flowcharacteristics, the location of one or more lesions or blockages,and/or the location of one or more interventional devices, e.g., stents,prosthetic valves, grafts, etc. In some embodiments, the model displaymay be, for example, within a digital window on a screen of terminal206. In further embodiments, the model display 210 may be on, forexample, a discrete screen that is a part of terminal 206, and that isseparate from, e.g., a recommendations display 208 screen.

The recommendations display 208 may be, for example, a visual display ofone or more recommendations for medical treatments received from therecommendation engine 216. In some embodiments, for example, therecommendations display may be a list of one or more recommendations forinterventions. In such embodiments, the recommendations display mayshow, for each entry in the list, the type of intervention beingrecommended and/or the name of the site for which the intervention isrecommended. In some embodiments, the recommendations display may alsoshow what intervention materials (e.g., a stent or other implant) areneeded. In some embodiments, the recommendations display may be adigital window display located adjacent to the model display 210. Infurther embodiments, the recommendations display may be integrated intothe model display 210, and may display a model of one or morerecommended interventions, generated, e.g., by interventions engine 116,on the model display 210. In further embodiments, the recommendationsdisplay may include, for example, a selectable list of one or morerecommendations for interventions, each of which, upon being selected,may be displayed in a visual model on model display 210.

One embodiment of the present disclosure uses patients' cardiac imagingto derive a patient-specific anatomical model of the patient's heart,vasculature, and/or features thereof, and update the geometric modelusing additional data received from one or more interventional and/ormeasurement devices. For example, FIG. 3 depicts a block diagram of anexemplary method 300 of anatomical modeling using information from aprocedure. The exemplary method depicted in FIG. 3 may be performed, forexample, by server systems 106. Specifically, as shown in FIG. 3, onemethod 300 for anatomical modeling using information from a medicalprocedure includes receiving an anatomical model and associatedcharacteristics in, e.g., electronic form (step 302). Method 300 mayfurther include displaying a representation of the model and associatedcharacteristics (step 304). Method 300 may further include displayingone or more recommended treatment options based on the model andassociated characteristics (step 306). Such recommended treatmentoptions may, for example, be generated by recommendations engine 118,and may be displayed on a recommendations display 208 adjacent to thedisplay of the model 210, on the terminal 206. Method 300 may alsoinclude receiving additional data (step 308), such as additionalmeasurements, patient-specific data, and/or interventional data from oneor more interventional and/or measurement devices 204. Method 300 mayfurther include determining a correspondence between the model and theadditional data (step 310). Such a correspondence may include, forexample, relating one or more points of additional data to one or moreaspects of the model. Method 300 may further include monitoring for adiscrepancy between the model and associated characteristics and theadditional data (step 312). Such a discrepancy may be, for example, amismatch between one or more points of additional data and acorresponding aspect of the model. If a discrepancy is not found, themonitoring step may be continued. If a discrepancy is found, then themodel and associated characteristics may be updated to remove or reducethe discrepancy (step 314). Updating the model and associatedcharacteristics may include, for example, adjusting an aspect of themodel corresponding to one or more points of additional data for which adiscrepancy was detected. Method 300 may further include displaying arepresentation of the updated model and associated characteristics (step316), for example, on the terminal 206. Method 300 may further includedisplaying one or more updated recommended treatment options to bedisplayed (step 318). Such updated recommended treatment options may beobtained from, for example, recommendations engine 118, which maygenerate the updated treatment options based at least in part on theupdated model and/or associated characteristics. Monitoring step 312 maybe repeated during or completion of the display of a representation ofthe updated model and/or updated recommended treatment options.

Method 300 will now be described in more detail below with reference toFIG. 3, including specific exemplary characteristics and exemplarysteps.

In one embodiment, the anatomical model and associated characteristicsreceived according to step 302 may be, for example, a patient-specificmodel of at least a portion of a system, such as a cardiovascularsystem. For example, the anatomical model may include a representationof any vascular system, anatomy, or subsystem, including, for example,coronaries, carotids, cerebral vessels, peripheral vessels, renalvessels, visceral vasculature, aorta, inner and outer vessel walls,plaque compositions, the left ventricle myocardium, the entire heart,muscle tissue, and/or organ tissue. The anatomical model may representvarious patient-specific aspects of a system, such as a patient-specificgeometry of any of the above systems, anatomies, or subsystems. Such ageometry may be represented as a list of points in space (possibly witha list of neighbors for each point) in which the space can be mapped tospatial units between points (e.g., millimeters). In one embodiment, theanatomical model may be, for example, a three-dimensional model.

Associated characteristics received according to step 302 may include,e.g., one or more estimates of, or known, physiological or phenotypicparameters of the patient, such as for example, patient age or patientgender. Associated characteristics may also include one or more bloodflow characteristics, cardiovascular risks, and/or biomechanicalcharacteristics at one or more locations in the anatomical model.Examples of such characteristics and/or risks include fractional flowreserve (FFR), coronary flow reserve (CFR), pressure, flow rate, flowvelocity, axial plaque stress, wall shear stress, oscillatory shearindex, plaque force, heart function (e.g., stroke volume, ejectionfraction, etc.), wall motion, heart, muscle, or organ perfusion, heartelectrophysiology characteristics (e.g., electrical propagation), plaquerupture risk, myocardium risk, cardiac and/or tissue perfusion,likelihood of progression or regression of plaques, likelihood ofcomplications, and/or pulsatile flow. Associated characteristics may bereceived from, e.g., physician systems 102, third party systems 104,storage devices 120, and/or processing devices 122, and/or may begenerated by the modeling engine 114 and/or the interventions engine 116using a generated anatomical model.

Associated characteristics may also be determined by calculations basedon the received anatomical model. For example, a characteristic such asa blood flow characteristic may be determined by performing, with theanatomical model, a three-dimensional blood flow simulation, reducedorder model blood flow simulation (e.g., a one-dimensional blood flowsimulation), a finite elements calculation, a biomechanical simulation,an electrophysiological simulation, estimation of simulated quantitiesand/or risks using machine learning from a database, etc.

The anatomical model and associated characteristics may be generatedand/or updated by, for example, modeling engine 114, using data (e.g.,images) stored in storage devices 120, data processed by processingdevices 122, and/or any measurement data 108, intervention data 110,and/or patient data 112 received from one or more physician systems 102and/or third party provider systems 104. For example, the modelingengine 114 may receive data from storage devices 120, processing devices122, physician systems 102, and/or third party systems 104, and mayconstruct a patient-specific anatomical model and determine associatedcharacteristics using that received data. In some embodiments, such datamay include, for example, images of a patient's anatomy obtainednoninvasively by, for example, a CT or CCTA procedure, an MRI, or anyother noninvasive procedure. In one embodiment, such data may be CCTAdata, and may be a set of images and/or data relating to a number of“slices” or cross-sections of a patient's heart. The modeling engine 114may then construct a three-dimensional image of the patient's heartusing the received slices. The modeling engine 114 may further run anFFR-CT (fractional flow reserve-computed tomography) analysis on thethree-dimensional image in order to further construct an anatomicalmodel of the patient's heart, and/or generate one or more associatedcharacteristics for the anatomical model. A FFR-CT analysis is morethoroughly discussed in, for example U.S. Pat. No. 8,315,812, filed onJan. 25, 2011 by Charles A. Taylor, which is incorporated herein byreference in its entirety. The modeling engine 114 may alternatively oradditionally run a CPR (curved planar reformation) analysis on thethree-dimensional image in order to further construct an anatomicalmodel of the patient's heart, and/or generate one or more associatedcharacteristics for the anatomical model.

Alternatively, other noninvasive imaging methods, such as magneticresonance imaging (MRI) or ultrasound (US), or invasive imaging methods,such as digital subtraction angiography (DSA), may be used to produceimages of the structures of the patient's anatomy. The imaging methodsmay involve injecting the patient intravenously with a contrast agent toenable identification of the structures of the anatomy. The resultingimaging data (e.g., provided by CCTA, MRI, etc.) may be provided from athird-party system 104, such as a radiology lab or a cardiologist, or bythe patient's physician system 102, etc. The image data may be stored bystorage devices 120 and/or processed by processing devices 122, as wellas being received by modeling engine 114. Methods of creating such amodel and determining associated characteristics are more fullydescribed in, for example, U.S. Pat. No. 8,315,812, which isincorporated herein by reference in its entirety. The anatomical modelmay be received, for example, in an electronic storage medium, such as adigital file or plurality of digital files.

Displaying the representation of the model according to step 304 mayinclude, for example, displaying a representation of the model on modeldisplay 210 of terminal 206. In some embodiments, the representation ofthe model may be a visual representation of the model as viewed from adesired angle and/or cross-section using, for example, three-dimensionalrendering, coloring, shading, plots, etc. In some embodiments, thevisual representation may include a three-dimensional rendering of theanatomical model, including, for example, a lumen surface, outer wallsurface, plaque, plaque composition, occlusions, heart, myocardialtissue, and/or other muscles or organs. In some embodiments, therepresentation of the anatomical model may be manipulable via an inputmethod. For example, terminal 206 may be equipped with a keyboard,mouse, touch-screen interface or other hardware configured to receiveuser input, and the representation of the anatomical model on the modeldisplay 210 may be rotated, enlarged, shrunken, or viewable from variouscross-sections. In another embodiment, displaying a representation ofthe anatomical model may include displaying the model from multipleangles, either simultaneously or in sequence. In another embodiment, therepresentation displayed according to step 304 may be a simplifiedversion of the anatomical model, e.g., a simplified diagram, a schematicrepresentation, and/or combinations thereof.

The associated characteristics displayed according to step 304 may be,for example, any of the associated characteristics received according tostep 302, and/or any associated characteristics generated by modelingengine 114 and/or intervention engine 116. The associatedcharacteristics may be displayed as an integrated part of the model,e.g., on the model display 210, and/or as annotations to therepresentation of the anatomical model, and/or as a list separate fromthe anatomical model, either on the model display 210 or on a separatescreen at, for example, terminal 206. For example, the location, size,and shape of a plaque in a coronary anatomical model may be representedby a geometry on the representation of the anatomical model. As anotherexample, vessel injury may be represented by a marking on the portion ofthe representation of the anatomical model corresponding to the site ofinjury, potentially in combination with an annotation and textdescribing the type of injury. As further examples, Reynolds numbers,Wolmsley numbers, and/or local flow rates may be represented byannotations on the model at the site to which they apply; alternately,one or more such characteristics may be represented by a list separatefrom representation of the model on model display 210.

The recommended treatment options displayed according to step 306 mayvary depending at least on the received anatomical model and associatedcharacteristics. Potential treatment options may include, for example, apossible stent location, bypass location, a rotablation, atherectomy,angioplasty, endarterectomy, PCI, coronary artery bypass grafting(CABG), carotid and/or peripheral intervention, renal and/or mesentericrevascularization, arteriovenous access procedures, location ofpacemaker leads, ablation sites, etc.

In some embodiments, the recommended treatment options may be generatedby, for example the recommendation engine 118, based on a plurality ofpotential treatment options received from one or more sources, such as,for example, physician systems 102, third-party systems 104, storagedevices 120, processing devices 122 and/or intervention engine 116, anyof which may store a plurality of treatment options, such asmedications, surgical procedures, and/or diagnostic procedures. Eachtreatment option may be associated with one or more types ofintervention data, such as indications for the treatment option, riskfactors, cost, probability of success, and/or any intervention data 110that may have been received from a physician system 102 or a third-partysystem 104.

In some embodiments, the recommendation engine 118 may receive ananatomical model and associated characteristics from the modeling engine114, and may generate a list of recommended treatment options based on aplurality of potential treatment options, the received anatomical model,and/or the associated characteristics. The recommended treatment optionsmay correspond to particular characteristics in the anatomical model,which the recommendation engine 118 may categorize as being of interest.For example, the recommendation engine 118 may recognize alower-than-optimal blood flow rate represented at a given locus in theanatomical model, and may generate a recommended treatment option havingintervention data indicating that the treatment option is designed toincrease blood flow rate at the given locus. As another example, therecommendation engine 118 may recognize the build-up of plaque at alocation in the anatomical model, and may add one or more recommendedtreatment options designed to remove the plaque.

In some embodiments, the recommendation engine 118 may determine arecommended treatment option by querying the intervention engine 116 togenerate an intervention model and associated characteristics of apotential treatment option, based on the anatomical model receivedaccording to step 302. The intervention engine 116 may model, forexample, the potential treatment option on the received anatomicalmodel, and may calculate one or more changes to associatedcharacteristics of the received anatomical model based on its generatedmodel of the potential treatment option on the received anatomicalmodel. The recommendation engine 118 may analyze the generatedintervention model and associated characteristics to determine whetherthe potential treatment results in an improvement to the anatomicalmodel, and based on its analysis, may or may not designate the potentialtreatment option as a recommended treatment option.

In further embodiments, the recommendation engine 118 may evaluate oneor more potential treatment options based on intervention dataassociated with the potential treatment option, such as the level ofrisk posed to the patient, the success rate of the treatment, etc. Therecommendation engine 118 may also evaluate one or more potentialtreatment options based on a combination of any of the above analyses ofthe potential treatment options.

In yet further embodiments, one or more treatment options may begenerated by a fully or partially automated system, such as thosedescribed in, for example, U.S. Pat. No. 9,449,146, filed on Jul. 3,2014 by Ryan Spilker et al., or U.S. Pat. No. 9,043,190, filed on Apr.16, 2014 by Leo Grady et al, both of which are incorporated by referenceherein in their entireties. In some embodiments, recommendation engine118 may include one or more such fully or partially automated systems.

In further embodiments, one or more treatment options may be suggestedor desired by a physician or other medical professional, and may bemanually added to the one or more recommended treatment options.

The recommended treatment options may be displayed as an integrated partof the model displayed on terminal 206. For example, the representationof the anatomical model displayed according to step 304 may be overlaidwith, or replaced by, a representation of one or more potentialinterventions on the anatomical model. The representation of one or morepotential interventions on the anatomical model may be generated by, forexample, intervention engine 116. Multiple recommended treatment optionsmay be displayed on the representation of the anatomical modelsimultaneously, or may be displayed one at a time. In an alternateembodiment, recommended treatment options may be displayed separately,e.g., as a list of selectable entries on a recommendations display 208.In some embodiments, each selectable entry on the recommendationsdisplay 208 may be viewed on the anatomical model displayed on the modeldisplay 210 when selected.

In some embodiments, the recommended treatment options may be scored toreflect the optimality of each possible treatment. Optimality of apossible treatment may be based, for example, on patient data, such asthe age of the patient, intervention data such as the success rate ofthe intervention, the ease of the intervention, stress factors on thepatient, etc., and/or potential improvements to the anatomical modelthat may result from the possible treatment. For example, theintervention engine 116 may model a potential stent position in theanatomical model, and may calculate that the distal vessel would achievean FFR greater than a cutoff of 0.8. The recommendation engine 118 maythen score the potential stent position accordingly, and/or may rank thepotential stent position among other potential treatment options inorder of optimality. In some embodiments, the optimality of one or morerecommended treatment options may be displayed along with the display ofone or more recommended treatment options according to step 306. Forexample, the one or more recommended treatment options may be displayedaccording to step 306 in order of optimality.

Additional data received according to step 308 may be any additionaldata pertaining to the anatomical model, associated characteristicsand/or the patient, including, for example, data received from one ormore interventional and/or measurement devices 204. Additional data mayrelate to, for example, viewing angles of an image (e.g., an angiogram),lumen size at one or more locations in the anatomical model, pressure orFFR at a location, blood flow rate at a location, heart rate, cardiaccontractility, plaque location or composition, wall motion, size andshape of a heart or other organ, necrosis or evidence of ischemia,electrical information (e.g., voltage, current, resistance, etc.),patient physiological state, heart function (e.g., stroke volume,ejection fraction, etc.), wall shear stress or axial plaque stress,force applied to a plaque, vessel wall, muscle, or organ, patientmotion, bypass grafting, or any other characteristic relevant to thereceived anatomical model.

In some embodiments, an interventional and/or measurement device 204 maybe configured to transmit additional data in the form of measurements,images, and/or other forms to the modeling engine 114, interventionengine 116, and/or recommendations engine 118. For example, aninterventional and/or measurement device 204 may be configured totransmit measurements, images, and/or other data to a physician system102 or a third party provider system 104 (as depicted in FIG. 1), whichmay then transmit the data to modeling engine 114, intervention engine116, and/or recommendations engine 118, e.g. over an electronic network101. In still further embodiments, an interventional and/or measurementdevice may be configured to transmit measurements, images, and/or otherdata to a physician system 102 or a third party provider system 104 (asdepicted in FIG. 1), which may then transmit the data to a processingdevice 120 and/or a storage device 122 (e.g. over an electronic network101), which may then transmit the data to modeling engine 114,intervention engine 116, and/or recommendations engine 118.

In still further embodiments, a physician or other practitioner may takedown data and/or measurements received from an intervention and/ormeasurement device onto a device, such as a computer, that is part of aphysician system 102, which may then transmit such data and/ormeasurements to one or more of a storage device 120, processing device122, modeling engine 114, intervention engine 116, and/orrecommendations engine 118.

Determining a correspondence between the model and the additional dataaccording to step 310 may be performed by, for example, a processingdevice 122, a modeling engine 114, and/or an intervention engine 116.Determining a correspondence may include, for example, identifying afeature or features of the anatomical model and/or associatedcharacteristics that are affected by the additional data. In someembodiments, the correspondence may be determined by performing aregistration of the additional data to a site of, or additionalcharacteristic of, the received anatomical model. For example, aphysician, an interventional and/or measurement device 204, processingdevice 122, modeling engine 114, and/or intervention engine 116 mayassign a locus to the additional data, the locus corresponding to aposition on the received anatomical model. In further embodiments, thecorrespondence may be determined by knowing the distance of aninterventional and/or measurement device 204 used to take the additionaldata from a landmark in the anatomical model (e.g., the distance of apressure wire from the aortic ostium).

In some embodiments, multiple types of additional data may be receivedfrom one or more interventional and/or measurement devices 204 or othersources. For example, additional data may be received from, e.g., both apressure wire and an angiogram. In such embodiments, the step ofdetermining a correspondence between the received anatomical model andthe additional data may be performed for each type of additional data.

Monitoring for a discrepancy between the anatomical model and associatedcharacteristics and the additional data according to step 312 may beperformed by, for example, the modeling engine 114, the interventionengine 116, and/or the processing devices 122. A discrepancy may be, forexample, a mismatch between one or more points of additional data andthe configuration of the received anatomical model, based on thecorrespondence determined between the additional data and the anatomicalmodel. The monitoring step 312 may be continued throughout, for example,an intervention or diagnostic procedure. In embodiments where multipletypes of additional data are received, the monitoring step 312 may beperformed with respect to each type of additional data and theanatomical model. The monitoring step may be performed intermittently orcontinuously, and may be performed while simultaneously performing anyof the other steps of method 300, e.g., steps 314-318.

Updating the model to remove a discrepancy according to step 314 mayinclude a variety of changes to the model depending on the discrepancyfound. For example, if additional data received from, e.g., anangiogram, OCT, or IVUS results in detection of a discrepancy of alesion size compared to a lesion size in the received anatomical model,the anatomical model may be updated to reflect the lesion size detectedinvasively.

As a further example, if additional data in the form of a blood pressuremeasurement from a pressure wire is different from a blood pressureshown in the received anatomical model, then the anatomical model may beupdated to include the blood pressure measured by the pressure wire.

As another example, if additional data in the form of a coronary flowmeasurement detected or predicted by a Doppler wire is different from acoronary flow in the received anatomical model, the anatomical model maybe updated to include the coronary flow measured or predicted by theDoppler wire.

As a further example, if additional data shows a cardiac contractilitythat differs from parameters used in the anatomical model, theanatomical model may be updated to include the measured cardiaccontractility.

As yet another example, if additional data shows a measured plaquecomposition, size and/or shape that are different from a plaquecomposition, size and/or shape in the received anatomical model, thenthe plaque size, composition, shape, force calculations, rupture risk,predicted plaque progression or regression, and/or myocardium at risk inthe anatomical model may be updated to reflect the measured plaquecomposition, size and/or shape received in the additional data.

As yet another example, if additional data shows a measured local heartviability that is different from a local heart viability in the receivedanatomical model, then local heart viability and electrophysiologicalpredictions may be updated in the anatomical model to reduce thediscrepancy.

As a further example, if additional data shows that a lesion modeled inthe anatomical model as a total occlusion is in fact subtotal, then theboundary conditions and blood flow characteristics in the anatomicalmodel may be recalculated.

As yet another example, if additional data reveals a patientphysiological state (e.g., hyperemia, rest, etc.), then boundaryconditions for the anatomical model may be updated and blood flowcharacteristics may be recalculated.

As still another example, if additional data relating to myocardial wallmotion indicates loss of tissue viability, a difference in motion, orstiffness, then the anatomical model may be updated such that the heartfunction, perfusion estimation, electrophysiological parameters, and/orboundary conditions for a blood flow characteristic computation may berecalculated.

As another example, if a stent is deployed during an interventionalprocedure and additional data is received reflecting the stentdeployment, then the anatomical model may be updated to reflect thepresence of the stent by, for example, changing the pressure differencesin an FFR-computed tomography calculation (FFR-CT).

As yet another example, if additional data received during, for example,a percutaneous coronary intervention (PCI) indicates FFR and lumendiameter values that are different from the FFR and lumen diametervalues in the anatomical model, then the inputs of an FFR-CT calculationfor an anatomical model may be adjusted to reduce the discrepancy. Forexample, an additional FFR-CT value may result in the percent stenosisover a vessel segment being retrofit.

Updating the associated characteristics may include, for example,determining a new or updated blood flow characteristic, biomechanicalcharacteristic, and/or risk score based on the updated model. Forexample, an updated blood flow characteristic, biomechanicalcharacteristic, and/or risk score may be calculated by performing, withthe updated anatomical model, a three-dimensional blood flow simulation,reduced order model blood flow simulation (e.g., a one-dimensional bloodflow simulation), a finite elements calculation, biomechanicalsimulation, electrophysiological simulation, estimation of simulatedquantities and/or risks using machine learning from a database, etc.

Displaying a representation of the updated model and associatedcharacteristics according to step 316 may be accomplished by, forexample, any of the methods described above with respect to displayingthe representation of the initial received model and associatedcharacteristics according to step 304. Additionally, displaying arepresentation of the updated model may include, for example, matching aviewing angle provided by additional data, such as a viewing angle froman image intensifier or an angiogram.

One or more updated recommended treatment options to be displayedaccording to step 318 may be determined based on the updated anatomicalmodel. Such updated recommended treatment options may be determined by,for example, recommendations engine 118, which may generate the updatedtreatment options based at least in part on the updated model and/orassociated characteristics, as was described above with respect to step306. For example, if additional data resulted in an updated lesion size,vessel size, or lesion composition in the anatomical model, then therecommendation engine 118 may recompute treatment options or equipmentchoices (e.g., catheter configuration, catheter shape choice, based onan updated aortic and/or coronary anatomy or configuration) based on theupdated anatomical model. As a further example, the recommendationengine 118 may re-evaluate the optimality of one or more recommendedtreatment options based on an updated model. For example, if additionaldata reveals that a stent was placed in one of two serial lesionsrepresented in an anatomical model, recommendation engine 118 mayevaluate or reevaluate the benefit of placing a stent in the secondserial lesion (e.g., optionally using intervention engine 116 to modelthe placement of a stent in the second serial lesion and the effect ofthe placement on one or more characteristics of an updated anatomicalmodel, such as a blood flow characteristic).

The steps of method 300 may be performed iteratively, or may beperformed simultaneously, repeatedly, and/or in real-time during, forexample, an interventional or diagnostic procedure. In some embodiments,not all steps of method 300 may be performed. In further embodiments, asubset of steps of method 300 may be performed repeatedly, while othersteps are performed only once or are not performed.

FIGS. 4A-4B depict a block diagram of a more detailed exemplary method400 for anatomical modeling using information from a procedure.According to step 402, a patient-specific vascular and/or anatomicalmodel may be received, for example, in an electronic storage medium.Such a vascular and/or anatomical model may be generated and/or updatedby, for example, modeling engine 114 according to any of the methodsdescribed herein (e.g., using images from a CCTA), and/or may beretrieved from storage devices 120 and/or processing devices 122.According to step 402, one or more blood flow characteristics,cardiovascular risks and/or biomechanical characteristics related to thevascular and/or anatomical data may be received. Such blood flowcharacteristics, cardiovascular risks and/or biomechanicalcharacteristics may be received from, for example, physician systems102, third party provider systems 104, storage devices 120, and/orprocessing devices 122, and/or may be generated and/or calculated bymodeling engine 114 using the vascular and/or anatomical model receivedaccording to step 402. For example, one or more blood flowcharacteristics may be computed by modeling engine 114 using an FFR-CTanalysis on the anatomical model and/or images and/or data receivedfrom, for example, physician systems 102, third party provider systems104, storage devices 120, and/or processing devices 122.

According to step 406, a representation of the model and associatedblood flow characteristics, cardiovascular risks, and/or biomechanicalcharacteristics may be displayed. Such a display may be according to,for example, any of the methods of display described herein with respectto method 300, e.g., using terminal 206, model display 210, and/orrecommendations display 208. According to step 408, a representation ofone or more interventional options may also be displayed on the model,using any of the methods previously described herein.

According to step 410, additional information pertaining to thepatient's vascular and/or anatomical data may be received from one ormore measurement devices. For example, additional information may bereceived from one or more interventional and/or measurement devices 204,as has been previously described herein. According to step 412, acorrespondence between the model and the additional information may bedetermined, as has been previously described herein. According to step414, the additional information and the model may be monitored for adiscrepancy between the two, by, for example, modeling engine 114,processing devices 122, intervention engine 116, or other processor.Upon a discrepancy being discovered, then according to step 416, themodel may be updated to remove or reduce the discrepancy by, forexample, using modeling engine 114. According to step 418, a new bloodflow characteristic, biomechanical characteristic, and/or risk scorebased on the updated model and/or additional information may bedetermined. For example, using the updated model, modeling engine 114may run a new FFR-CT analysis using the updated model to obtain a newblood flow characteristic, biomechanical characteristic, and/or riskscore. According to step 420, the display of the representation of themodel on, for example, model display 208 of terminal 206 may be updatedbased on the updated model. According to step 422, the new blood flowcharacteristic, biomechanical characteristic, and/or risk score may beoutput to an electronic display and/or electronic storage device, suchas, for example, terminal 206 or storage devices 120. According to step424, the display (e.g., model display 210) may be updated to reflectchanges in anatomy, a computed blood flow characteristic, biomechanicalcharacteristic, and/or risk score. According to step 426, therepresentation of one or more interventional options may be updatedbased on the model by, for example, intervention engine 116. Accordingto step 428, recommended treatment options or equipment choices may beupdated based on the model. For example, recommendation engine 118 maygenerate or update a plurality of recommended treatment options orequipment choices based on, e.g., the updated model and/or a change inanatomy, blood flow characteristic, biomechanical characteristic, and/orrisk score. More additional information may be received, according tostep 414, to which steps 416-428 may be applied.

The steps of method 400 may be performed iteratively, or may beperformed simultaneously, repeatedly, and/or in real-time during, forexample, an interventional or diagnostic procedure. In some embodiments,not all steps of method 400 may be performed. In further embodiments, asubset of steps of method 400 may be performed repeatedly, while othersteps are performed only once or are not performed.

In some embodiments, the steps of methods 300 and 400 may additionallyallow a user, such as a physician or other medical professional, tostore and/or retrieve one or more received anatomical models and/orassociated characteristics, displayed recommended treatment options,updated anatomical models and/or associated characteristics, and/orupdated recommended treatment options, using, for example, an inputdevice in conjunction with terminal 206 such as a keyboard, mouse,and/or touch-screen interface.

In alternate embodiments, the functions of modeling engine 114,intervention engine 116, and recommendation engine 118 may not be splitapart into separate discrete categories, but may instead be shared andperformed by one or more computer processors.

An exemplary form of the disclosure herein will now be described. Apatient-specific vascular and/or anatomical model in an electronicstorage medium (e.g., a network drive, hard drive, cloud drive, mobilephone, tablet, etc.) may be received, showing a flow fractional reservecomputerized tomography (FFR-CT) map and/or curved planar reformation(CPR) images of a plaque and/or vessel wall. One or more stents may thenbe introduced into the anatomy of the patient represented by thepatient-specific vascular and/or anatomical model, in a position andsequence selected by a medical professional. The patient-specificvascular and/or anatomical model showing the FFR-CT map and/or CPRimages may be displayed on an image screen, such as a computer monitor.The model may be updated as each stent is deployed to reflect thepresence of the stent and its effect on the vasculature and/or anatomyrepresented in the model (e.g., changes in pressure differences in theFFR-CT map). The model may be rotated periodically on the display, andmay be updated constantly and/or at each rotation of the model so thatthe model is synchronized with real-time physical changes (e.g.,placement of the one or more stents). A list of procedural options toimprove the quality and/or speed of a procedure, and/or the outcome of aprocedure, may be provided in real-time during insertion of the one ormore stents. This updating may include, but is not limited to, enablinga user to perform virtual stenting to predict stenting solutions,enabling a user to store, retrieve, and/or display stenting options,enabling a user to perform stent solutions at will during the course ofa procedure, and/or updating a “current status” solution, which may befixed after each new stent is deployed and in place.

Any aspect set forth in any embodiment described herein may be used withany other embodiment set forth herein. Every method step set forthherein may be performed by any single computer processor and/or serveror combination of computer servers and/or processors, and may becompleted local to a given location or remotely on any suitable computerprocessor, combination of computer processors, interactive display ordisplays, monitor(s) or screen(s).

It will be apparent to those skilled in the art that variousmodifications and variations can be made in the disclosed systems andprocesses without departing from the scope of the disclosure. Otherembodiments will be apparent to those skilled in the art fromconsideration of the specification and practice of the disclosuredisclosed herein. It is intended that the specification and examples beconsidered as exemplary only, with a true scope and spirit of thedisclosure being indicated by the following claims.

We claim:
 1. A method of automatically updating an anatomical model,comprising: using a processor to determine a correspondence betweenpatient-specific data and at least one of a patient-specificthree-dimensional anatomical model or at least one characteristicassociated with the three-dimensional anatomical model; using theprocessor to identify a discrepancy between the patient-specific dataand at least one of the three-dimensional anatomical model or the atleast one associated characteristic; using the processor to modify atleast one of the three-dimensional anatomical model or the at least oneassociated characteristic to reduce the discrepancy; using the processorto generate at least one recommendation of an intervention on thepatient based on at least one of the three-dimensional anatomical modelor the at least one associated characteristic; and using the processorto transmit the at least one recommendation to a display unit.
 2. Themethod of claim 1, further comprising: using the processor to model anintervention or a part thereof on the anatomical model; and using theprocessor to transmit a representation of the modeled intervention orpart thereof to the display unit.
 3. The method of claim 2, wherein theintervention includes one or more of: an insertion of an endoscopicdevice, a laparoscopic device, a stent, a prosthetic implant, a graft,or a needle; a bypass grafting procedure; a rotablation; an atherectomy;an angioplasty; an endarterectomy; a percutaneous coronary intervention;a carotid intervention; a peripheral intervention; a renalrevascularization; a mesenteric revascularization; or an arteriovenousaccess procedure.
 4. The method of claim 1, wherein the patient-specificdata is from a medical procedure and the medical procedure is aninvasive procedure.
 5. The method of claim 1, wherein thepatient-specific data is from a medical procedure and the medicalprocedure is a diagnostic procedure.
 6. The method of claim 1, whereinthe at least one associated characteristic is a blood flowcharacteristic, a location of one or more lesions or blockages, or alocation of one or more interventional devices.
 7. The method of claim1, wherein the patient-specific data includes at least one of: data froman angiogram; data from optical coherence tomography; data from anintravenous ultrasound; blood pressure data; coronary flow data; cardiaccontractility data; a measurement of a plaque; a local heart viability;data showing whether an occlusion is total or subtotal; data relating tothe patient's physiological state; data relating to myocardial wallmotions; stent position data; or data from a percutaneous coronaryintervention.
 8. The method of claim 1, wherein using the processor todetermine a correspondence between the patient-specific data and atleast one of the three-dimensional anatomical model or the at least oneassociated characteristic comprises using the processor to determine alocation of the anatomical model to which the patient-specific data mayapply.
 9. The method of claim 1, wherein the display unit is located ina medical facility.
 10. A computer-implemented method for automaticallyupdating an anatomical model, the method comprising: using a processorto determine a correspondence between patient-specific data and at leastone of a patient-specific three-dimensional anatomical model or at leastone characteristic associated with the three-dimensional anatomicalmodel; using the processor to locate a discrepancy between thepatient-specific data and at least one of the anatomical model or the atleast one associated characteristic; updating, using the processor, atleast one of the anatomical model or the at least one associatedcharacteristic to reduce the discrepancy; using the processor togenerate at least one recommendation of an intervention on the patientbased on at least one of the three-dimensional anatomical model or theat least one associated characteristic; and using the processor totransmit the at least one recommendation to a display unit.
 11. Themethod of claim 10, wherein the at least one associated characteristicis a blood flow characteristic.
 12. The method of claim 10, furthercomprising: using the processor to model the intervention on theanatomical model; and using the processor to transmit a representationof the modeled intervention to the display unit.
 13. The method of claim10, wherein the patient-specific data is from an interventionalprocedure, and the method further comprising: periodically receiving, atthe processor, refreshed patient-specific data from the interventionalprocedure; using the processor to monitor for a new discrepancy betweenthe refreshed patient-specific data and at least one of the anatomicalmodel or the at least one associated characteristic; and if a newdiscrepancy is found: updating, using the processor, at least one of theanatomical model or the at least one associated characteristic to reducethe new discrepancy.
 14. An anatomical modeling system comprising aprocessor, wherein the processor is configured to: determine acorrespondence between patient-specific data and at least one of apatient-specific three-dimensional anatomical model or at least onecharacteristic associated with the three-dimensional anatomical model;identify a discrepancy between the patient-specific data and at leastone of the three-dimensional anatomical model or the at least oneassociated characteristic; modify at least one of the three-dimensionalanatomical model or the at least one associated characteristic to reducethe discrepancy; generate at least one recommendation of an interventionon the patient based on at least one of the three-dimensional anatomicalmodel or the at least one associated characteristic; and transmit the atleast one recommendation to a display unit.
 15. The system of claim 14,wherein the patient-specific data is from an interventional procedure,and the processor is further configured to: periodically receiverefreshed patient-specific data from the interventional procedure;monitor for a new discrepancy between the refreshed patient-specificdata and at least one of the three-dimensional anatomical model or theat least one associated characteristic; and if a new discrepancy isfound: update at least one of the three-dimensional anatomical model orthe at least one associated characteristic to reduce the newdiscrepancy.
 16. The system of claim 14, wherein the at least oneassociated characteristic is a blood flow characteristic.
 17. The systemof claim 15, wherein the processor is further configured to: generate amodel of the intervention on the anatomical model; and transmit arepresentation of the modeled intervention to the display unit.